In situ and remote sensing of turbulence in support of the aviation community. Larry B. Cornman National Center for Atmospheric Research USA

Similar documents
Turbulence Measurements. Turbulence Measurements In Low Signal-to-Noise. Larry Cornman National Center For Atmospheric Research

Measuring In-cloud Turbulence: The NEXRAD Turbulence Detection Algorithm

NEXRAD Turbulence Detection Algorithm (NTDA) and CIT Avoidance Guidelines and D-CIT Development. FY 2008 Year-End Status Report

system & Royal Meteorological Society Meeting at Imperial College, London 15 Jan 2014 Robert Sharman NCAR/RAL Boulder, CO USA

SATELLITE SIGNATURES ASSOCIATED WITH SIGNIFICANT CONVECTIVELY-INDUCED TURBULENCE EVENTS

NTDA Development and Operational Demonstration

Weather Technology in the Cockpit (WTIC) Program Program Update. Friends/Partners of Aviation Weather (FPAW) November 2, 2016

ipads/efbs and Weather the cockpit Captain Joe Burns Managing Director United Airlines Technology and Flight Test

REMOTE DETECTION AND REAL-TIME ALERTING FOR IN-CLOUD TURBULENCE

FAA Weather Research Plans

Weather Technology in the Cockpit (WTIC) Shortfall Analysis of Weather Information in Remote Airspace Friends and Partners of Aviation Weather Summer

Advanced Weather Technology

Automated in-situ Turbulence reports from Airbus aircraft. Axel PIROTH

Remote Oceanic Meteorology Information Operational (ROMIO) Demonstration

Turbulence Avoidance Technologies

Insert Title Here Presented by: Steve Abelman Manager of Weather Technology, American Airlines

Emerging Aviation Weather Research at MIT Lincoln Laboratory*

AOPA. Mitigating Turbulence Impacts in Aviation Operations. General Aviation Perspective

Reprint 797. Development of a Thunderstorm. P.W. Li

Progress in Aviation Weather Forecasting for ATM Decision Making FPAW 2010

Strengthening the CDM triad: A view from the cockpit

Translating Meteorological Observations into Air Traffic Impacts in Singapore Flight Information Region (FIR)

Global Response of Clear-Air Turbulence to Climate Change. Professor Paul D. Williams University of Reading, UK

Strengthening the CDM triad: A view from the cockpit

Global aviation turbulence forecasting using the Graphical Turbulence Guidance (GTG) for the WAFS Block Upgrades

Future Aeronautical Meteorology Research & Development

Calculates CAT and MWT diagnostics. Paired down choice of diagnostics (reduce diagnostic redundancy) Statically weighted for all forecast hours

Satellite-based Convection Nowcasting and Aviation Turbulence Applications

NUMERICAL SIMULATION OF A CONVECTIVE TURBULENCE ENCOUNTER

Advances in Weather Technology

Weather Impact Modeling. Based on Joe Mitchell s slides

P1.1 THE NATIONAL AVIATION WEATHER PROGRAM: AN UPDATE ON IMPLEMENTATION

Strategic Radar Enhancement Project (SREP) Forecast Demonstration Project (FDP) The future is here and now

INTEGRATED TURBULENCE FORECASTING ALGORITHM 2001 METEOROLOGICAL EVALUATION

Montréal, 7 to 18 July 2014

AIR TRAFFIC MANAGEMENT DECISION SUPPORT USING INTEGRATED METHODS OF DIAGNOSING AND FORECASTING AVIATION WEATHER

Advances in weather and climate science

FPAW October Pat Murphy & David Bright NWS Aviation Weather Center

Update on CoSPA Storm Forecasts

Transitioning NCAR s Aviation Algorithms into NCEP s Operations

Weather in the Connected Cockpit

AN AIRCRAFT ENCOUNTER WITH TURBULENCE IN THE VICINITY OF A THUNDERSTORM

0-6 hour Weather Forecast Guidance at The Weather Company. Steven Honey, Joseph Koval, Cathryn Meyer, Peter Neilley The Weather Company

Regional Hazardous Weather Advisory Centres (RHWACs)

2.4 The complexities of thunderstorm avoidance due to turbulence and implications for traffic flow management

Synthetic Weather Radar: Offshore Precipitation Capability

New Meteorological Services Supporting ATM

Simulations of Midlatitude and Tropical Out-of-Cloud Convectively-Induced Turbulence

Consolidated Storm Prediction for Aviation (CoSPA) Overview

WAFC London Research and Development (R&D) Plans for algorithm development UK Met Office

National Convective Weather Forecasts Cindy Mueller

An Initial Assessment of a Clear Air Turbulence Forecasting Product. Ankita Nagirimadugu. Thomas Jefferson High School for Science and Technology

Recap of the NTSB PIREP Forum: Optimizing Safety Benefits for Pilots, ATC, and Meteorologists. Paul Suffern NTSB Meteorologist

NWP in aviation: CAT diagnostics

Regional Hazardous Weather Advisory Centres (RHWACs)

Oceanic Weather Product Development Team

WWRP Implementation Plan Reporting AvRDP

WAFS_Word. 2. Menu. 2.1 Untitled Slide

R. Sharman*, L. Cornman, J. Williams National Center for Atmospheric Research, Boulder, CO, 80307

Friends and Partners of Aviation Weather Fall Meeting Turbulence Session

Weather Needs for UAS Operations

Utilising Radar and Satellite Based Nowcasting Tools for Aviation Purposes in South Africa. Erik Becker

Amy Harless. Jason Levit, David Bright, Clinton Wallace, Bob Maxson. Aviation Weather Center Kansas City, MO

Complementary Use of Airborne Wx Radar & Datalink Graphical Wx

WMO Aviation Research Demonstration Project (AvRDP) and Seamless Trajectory Based Operation (TBO) PW Peter Li

Remote Sensing of Turbulence: Radar Activities. FY04 Year-End Report

Using McIDAS-V for Satellite-Based Thunderstorm Research and Product Development

Overview on project activities with regard to thunderstorms

NCAR UCAR. 50 th Anniversary Lecture

7.1 The Schneider Electric Numerical Turbulence Forecast Verification using In-situ EDR observations from Operational Commercial Aircraft

10.2 RESULTS FROM THE NCAR INTEGRATED TURBULENCE FORECASTING ALGORITHM (ITFA) FOR PREDICTING UPPER-LEVEL CLEAR-AIR TURBULENCE

NAM-WRF Verification of Subtropical Jet and Turbulence

Weather Considerations for UAS Integration

Doppler Weather Radars and Weather Decision Support for DP Vessels

United Airlines Vision for Weather Decision Making

The WMO Aviation Research & Demonstration Project (AvRDP) at Paris-CDG airport. Pauline Jaunet Météo-France

Characterization of Forecast Uncertainty by Means of Ensemble Techniques

Improving real time observation and nowcasting RDT. E de Coning, M Gijben, B Maseko and L van Hemert Nowcasting and Very Short Range Forecasting

FLYSAFE meteorological hazard nowcasting driven by the needs of the pilot

Blend of UKMET and GFS 3hr increments F06 to F degree downloadable grid available on WIFS

NOAA s Severe Weather Forecasting System: HRRR to WoF to FACETS

Date: October 31, 2012

Editor's Note: This article first appeared in Twin & Turbine, May 2005, and is reprinted here by permission.

NTDA Operational Demonstration. Turbulence PDT Task FY 2005 Year-End Progress Report

WMO Aeronautical Meteorology Scientific Conference 2017

Weather Evaluation Team (WET)

Aircraft-based Observations: Impact on weather forecast model performance

Deputy Director for Science NCAR Aviation Applications Program

Aviation Weather Services (AJW-94)

Verification and performance measures of Meteorological Services to Air Traffic Management (MSTA)

En-route aircraft wake vortex encounter analysis in a high density air traffic region

Explosive volcanic eruptions in the North Pacific: Interactions between the Alaska Volcano Observatory and Volcanic Ash Advisory Centers

Weather Vision: Past, Present, Future. Joint Planning and Development Office (JPDO) Weather Integrated Product Team

Multi-Function Display Pilot s Guide Addendum

Cross-cutting Issues Impacting Operational ATM and Cockpit Usability of Aviation Weather Technology. John McCarthy Sherrie Callon Nick Stoer

Weather Products for Decision Support Tools Joe Sherry April 10, 2001

WMO Aeronautical Meteorology Scientific Conference 2017

8.7 Calculation of windshear hazard factor based on Doppler LIDAR data. P.W. Chan * Hong Kong Observatory, Hong Kong, China

Observations and simulations of turbulent processes in the upper troposphere and lower stratosphere

Weather Legends in FOREFLIGHT MOBILE

Transcription:

In situ and remote sensing of turbulence in support of the aviation community Larry B. Cornman National Center for Atmospheric Research USA

The Motivation Turbulence is the main cause of in-flight injuries for both passengers and flight attendants. After a severe encounter, the airline has to perform a structural check on the aircraft. Pilots will try to re-route around an area if there have been reports of moderate or greater turbulence. Tstorm & windshear Icing Precip Ceil & Vis Part 121 Other Turbulence Bottom-line: Turbulence is a safety problem as well as having a large financial impact on the airlines. Weather-related accidents for large transport aircraft

DC-8 Cargo Aircraft Damaged Due to Extreme Turbulence Missing Something?

The Turbulence Problem for Aviation (Grossly Oversimplified) Turbulent eddies larger than 100 meters and smaller than 3000 meters (approximately) produce aircraft motions which can be difficult -- or impossible -- to control. With small-amplitude eddies, these induced motions may be simply uncomfortable to passengers. Large amplitude eddies, on the other hand, can result in passenger injuries or even structural damage to the aircraft.

Turbulence Scales of Motion Large eddies Turbulent eddies Small eddies 10 s km Aircraft responds to scales from approx. 100 m 3 km cm NWP resolution Mesoscale model resolution Fine-scale model resolution

The product of the response function and the wind spectrum gives the output spectrum. Response Function for Transport Aircraft 2000 m 100 m Von Karman Spectra

The Need For Turbulence Measurements Tactical: Real time alerts of eminent encounter (< 1 min.) Turn seat belt sign on. Get passengers seated and in seatbelts. Get service carts stowed and flight attendants seated. Real time alerts/nowcast of impending encounter (< 15 min.) All of the above. Change altitude. Change flight path.

The Need For Turbulence Measurements Strategic: Nowcast/Forecast of potential encounter (en route) Increase pilot awareness. Discussions with airline Dispatch personnel. Discussions with en route air traffic personnel. Consider altitude/course change. Forecast of potential encounter (pre-flight) Pre-flight awareness for pilot/dispatch. Consider re-routing flight path.

In situ Turbulence Measurement and Reporting System Goal: To augment/replace subjective PIREPs with objective and precise turbulence measurements. Features: Atmospheric turbulence metric: eddy dissipation rate (EDR). EDR can be scaled into aircraft turbulence response metric (RMS-g). Adopted as ICAO Standard

Increase in Spatial/temporal Coverage: UAL EDR Reports Compared to pireps 1.3 million EDR reports/month from 100 or so aircraft - compared to 55k pireps from all aircraft. 737 757 737 + 757

In situ measurement and reporting system Implemented on ~ 200 UAL aircraft since 2000 Implementation status SWA: Fleet implementation on ~ 280 737-700s in CY08 DAL: Fleet implementation on ~ 120 737-800s in CY08 NWA: Discussions ongoing for implementation on ~ 140 Airbus 319/320s and 56 787s UAL: 757 ACMS replacement AAL: Discussions ongoing Website: UAL 757 edr flight tracks overlaid on GTG forecasting product

NASA Airborne Radar Detection of Turbulence Program RMS winds RMS g-load From NASA B-757 Aircraft 19:12:02 19:13:44

Event 232-10 (19:12:02, 19:12:13, 19:12:25) -1:42-1:31-1:19 Hazard detected 1:19, 18 km to encounter

Event 232-10 (reflectivities at 19:12:25) -1:19

Event 232-10 (19:12:37, 19:12:49, 19:13:01) -1:07-0:55 Persistent detection -0:43

Flight Track for NASA flight R232 Event R232-10 North-Central Alabama

NEXRAD in-cloud turbulence detection algorithm (NTDA) Cockpit display or radioed alert Graphic courtesy of virtualskies.arc.nasa.gov Dispatch, ATC, etc. NEXRAD or TDWR In-cloud edr display

Case Study: Severe turbulence encounter at FL 310 over NE Arkansas Vertical acceleration from -0.9 g to +2.3 g in about 3 seconds 43 minor injuries, two serious; cabin damage 8 min. warning could have reduced/eliminated injuries X X

NTDA uplink demonstration Uses data from 83 NEXRADs, covering eastern US 3-D EDR mosaic updated every 5 minutes, displayed via Experimental ADDS ACARS text uplinks to UAL cockpits for flights registered on NCAR webpage Pilot feedback via webpage September press release garnered significant attention /EXPERIMENTAL TURBULENCE FI UAL /AN N UA UPLINK -- 05 Sep 2006 21:38:13Z FL 300 orient. 83 deg '+'=waypoint, '*'=route, 'X'=aircraft at 38.3N, 80.6W ' '=no_data, 'o'=smooth, 'l'=light, 'M'=mod, 'S'=severe -----------------------(52 to IAD)------------------------ * * MM * MM * MM l lll M * MMM lollo * lml oolo * l oo * * 080 * M llllllll ll * MM lllllllllllllll l * lll lllllllllollllllll * MMl l MMllllllllooollllll * MMl l MMMl lllllllllollll * MM l MMMM llll llol ll * MM MMMM ll * MMS MMM * MSS MM * MSS +PUTTZ + MSS * SSSSSS MSS M l S*SSSSSSSSS MSS M llls*sssmsssss MSS l lsms*smmmmssss MSS l SSMM*MMMMMMMM MSS M MM*SMMMMMMMMlllll MSS M M*SSMMMMMMMMllllll MMM M *MMMMMMMMMMMMMllll MMM * MMlllMMMlMllllllM lll 040 * lllllllllllllllllmml lll * llllllllllllll lls * llllllllll MMS * lllllll SSS * lllll SSS * lll MMS * l ll MM * MM M MM*MM o MSS SM*MM MMM MM *MM l MM MMMSS S * l l lm MMMSSM * lllllll o l l MMMM * lllllo MMMMM * llllll M * lllll SSS * llll ll SSS M l * l lll SSS Mlllll * llm MM lmlllll * l ------- ---------valid- --------X-------- ---------------- -90 +90 Left 40 2135Z (18 from 3819N/8058W) Right 40 Flight information Legend Route Waypoint Severe turbulence Moderate turbulence Aircraft position Vertical cross-section

Diagnosis of convectively-induced turbulence (DCIT) Near-storm environment and turbulence diagnostics from RUC Storm location, morphology, and observations from satellite, radar (dbz and EDR), and lightning Associations with in situ EDR reports used to tune an empirical model (random forest) DCIT provides tactical 3-D gridded EDR, Prob MoG and Prob SoG assessments for use in GTGN DCIT real-time prototype running in RAL since August DCIT: Prob MoG (uncalibrated) 27 June 2007 2300 UTC, FL 300 RUC only RUC+obs

Turbulence Detection via Airborne GPS Receivers: The Concept Airborne receivers would be a platform of opportunity to collect occultations in the cruise regime of commercial aviation, e.g., 20-40 kft. AGL. The turbulence measurements from these occultations would probably not be used as stand-alone information, but integrated into operational nowcast/forecast products.

Geometry of the Problem η 1 R η 1 1 is the distance, along the LOS, from the satellite to the center of the turbulence patch. R is the distance from the satellite to the aircraft receiver along LOS. Δη is the width of the turbulence patch along LOS. R η 1 is the distance from the aircraft to the turbulence patch. Δη R η

Aircraft Flight Track with GPS Occultations

Parameter Estimation 1000 realizations Maximum Likelihood (ML) estimation of intensity with fixed R η1 = 100 km while varying L0. Horizontal and vertical lines are simulated (i.e., true ) values.

Parameter Estimation (cont d) 1000 realizations ML estimation of intensity with fixed while varying. R η 1 L 0 = 3 km

Initial ML estimation of intensity (left) and using an estimate of (right). η 1 Solid vertical line is true value. Blue values are from using the high-frequency portion of the spectrum, red values use all the spectral points. R η 1 Simulated value is 100 km, guess is 10 km - i.e., an underestimate hence the overestimate of the intensity.

Detection of Turbulence Using an Airborne Forward-Looking IR Sensor Possible Approach: Derive equation that relates the statistics of the atmospheric turbulence (e.g., temperature field) to those of the sensor measurables. Consider the irradiance (H) at a given frequency, measured at the aircraft (x=0): 0 H (0) = WB ( T ( x)) f ( x) dx L Where W B is the Planck function, L is the path length over which the measurement is made, and f is a combined function of the nonturbulent atmosphere and the response characteristics of the sensor.

Detection of Turbulence Using an Airborne Forward-Looking IR Sensor Next, consider the same measurement when the aircraft has moved a distance ρ : ρ H ( ρ) = WB ( T( x)) f( x) dx L+ ρ Assuming that the Planck function is linear in the temperature, the correlation function of the irradiances can be computed: 0 ρ H (0) H( ρ) K T( x) T( x ) f( x) f( x ) dxdx = LL+ ρ

Detection of Turbulence Using an Airborne Forward-Looking IR Sensor Assuming that standard turbulence theory applies, 2 T( x) T( x ) = CT g( x x) 2, where C T is the intensity parameter of the turbulent temperature field. In principle the turbulence intensity parameter is given by: C 2 T = 0 ρ H(0) H( ρ ) K g( x x) f ( x) f ( x ) dxdx LL+ ρ

Detection of Turbulence Using an Airborne Forward-Looking IR Sensor Issues: Aircraft respond to vertical wind motions, not temperature fluctuations - the relationship between the two is not well-understood. To what spatial scales are these IR devices sensitive?

Turbulence Forecast Product: Graphical Turbulence Guidance (GTG) Based on RUC NWP forecasts Uses a combination of turbulence diagnostics, merged and weighted according to current performance (pireps, EDR) Current work areas: Probabilistic forecasts of moderate-or-greater (MOG) turbulence Optimal use of in situ reports Output probability of MOG,SOG > some EDR threshold Improve forecasts of severe turbulence

Ellrod1 DTF3 UBF Ri -NVA NCSU1 GTG = Weighted ensemble of turbulence diagnostics FRNTGth CLIMO NCSU2 GTG VWS TEMPG EDRS10 0 h forecast valid at 22 Sep 2006 15Z

GTG improvement using in situ data over pireps Null MOG w/ Pireps w/ In Situ ROC Curve Intensity Discrimination

Turbulence Nowcasting System (GTG-N) Overview Motivation: GTG updates are tied to the model runs (once per hour). Turbulence can vary dramatically over small space/time intervals. We will have more observational data and rapidupdate diagnostic products in the near future. This implies the need for a rapid-update (e.g., every 15 min) gridded turbulence product, GTG-N

GTG-N Overview Approach (nominal): Start with GTG grid. Incorporate: DCIT/NTDA In situ Reports Pireps Lightning data Satellite data. Other Compute confidences for all inputs (diagnostic and measurements). Use an intelligent merging procedure to create a unified turbulence nowcast gridded product.

Turbulence Nowcasting System: GTG-N Merges all current turbulence observations with forecast grids. Cockpit display or alert (EDR or RMS-g) Graphic courtesy of virtualskies.arc.nasa.gov Dispatch, ATC, etc. In situ EDR reports, PIREPs, 4D data cube updated every ~15 min GTG forecast grids (EDR) Convective turbulence diagnostic (EDR) Radar (NTDA) turbulence grids (EDR) Wx satellite data

GTG-N Example GTG 1 hr forecast blend DCIT pireps In situ tracks

Summary Turbulence measurements are critical in providing accurate and operationally useful tactical and strategic information to users. In situ turbulence measurements are now available and used operationally more to come. A number of proof-of-concept sensor demonstrations have occurred, with positive results. Other technologies in development/evaluation: Airborne lidar Satellite GPS/Iridium Airborne IR